AI-Agents: Automation & Business with LangChain & LLM Apps Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview (80-120 words) describing structure and time commitment.
Module 1: AI Agent Fundamentals
Estimated time: 0.5 hours
- Overview of AI agent frameworks: LangChain, LangFlow, LangGraph, Autogen, BabyAGI, CrewAI
- Introduction to LLMs: GPT-4, Claude, Gemini, Llama 3, Mistral
- Understanding function calling in LLMs
- Core concepts of agent autonomy and task execution
Module 2: Tools, Vector DBs & RAG
Estimated time: 1 hour
- Setting up vector databases for semantic search
- Generating embeddings for custom data retrieval
- Training agents using PDFs, CSVs with LlamaIndex and LlamaParse
- Integrating Flowise and Node tools for RAG pipelines
Module 3: Building Agents & Automation
Estimated time: 1.25 hours
- Creating AI agents for content generation and email automation
- Developing lead research agents with real-time data fetching
- Connecting APIs using Python and JavaScript for task automation
- File handling and workflow orchestration with Make.com
Module 4: Flowise & Custom Integration
Estimated time: 1 hour
- Installing and configuring Flowise with Node.js
- Building function-calling agents for Gmail integration
- Integrating calculator, Serper, and Microsoft Copilot tools
Module 5: Business Applications & Deployment
Estimated time: 1 hour
- Deploying AI agents on websites and as standalone tools
- Developing marketing strategies for AI-powered solutions
- Setting pricing models and managing customer acquisition
Module 6: Security, Compliance & Open-Source LLMs
Estimated time: 0.75 hours
- Preventing prompt injection and data poisoning attacks
- Ensuring privacy and copyright compliance in AI workflows
- Using Ollama, Llama 3.1, and model selection strategies
Prerequisites
- Basic understanding of Python or JavaScript
- Familiarity with APIs and web development concepts
- Access to a code editor and command-line interface
What You'll Be Able to Do After
- Build secure, business-ready AI agents using LangChain and Flowise
- Implement RAG systems with custom data sources and vector databases
- Automate real-world tasks like email campaigns and lead generation
- Deploy AI agents on websites or as standalone applications
- Apply monetization strategies and security best practices to AI products